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strands.types.tools

Tool-related type definitions for the SDK.

These types are modeled after the Bedrock API.

Type alias for JSON Schema dictionaries.

class ToolSpec(TypedDict)

Defined in: src/strands/types/tools.py:23

Specification for a tool that can be used by an agent.

Attributes:

  • description - A human-readable description of what the tool does.
  • inputSchema - JSON Schema defining the expected input parameters.
  • name - The unique name of the tool.
  • outputSchema - Optional JSON Schema defining the expected output format.
  • Note - Not all model providers support this field. Providers that don’t support it should filter it out before sending to their API.
class Tool(TypedDict)

Defined in: src/strands/types/tools.py:41

A tool that can be provided to a model.

This type wraps a tool specification for inclusion in a model request.

Attributes:

  • toolSpec - The specification of the tool.
class ToolUse(TypedDict)

Defined in: src/strands/types/tools.py:53

A request from the model to use a specific tool with the provided input.

Attributes:

  • input - The input parameters for the tool. Can be any JSON-serializable type.
  • name - The name of the tool to invoke.
  • toolUseId - A unique identifier for this specific tool use request.
  • reasoningSignature - Token that ties the model’s reasoning to this tool call.
class ToolResultContent(TypedDict)

Defined in: src/strands/types/tools.py:70

Content returned by a tool execution.

Attributes:

  • document - Document content returned by the tool.
  • image - Image content returned by the tool.
  • json - JSON-serializable data returned by the tool.
  • text - Text content returned by the tool.

Status of a tool execution result.

class ToolResult(TypedDict)

Defined in: src/strands/types/tools.py:90

Result of a tool execution.

Attributes:

  • content - List of result content returned by the tool.
  • status - The status of the tool execution (“success” or “error”).
  • toolUseId - The unique identifier of the tool use request that produced this result.
class ToolChoiceAuto(TypedDict)

Defined in: src/strands/types/tools.py:104

Configuration for automatic tool selection.

This represents the configuration for automatic tool selection, where the model decides whether and which tool to use based on the context.

class ToolChoiceAny(TypedDict)

Defined in: src/strands/types/tools.py:114

Configuration indicating that the model must request at least one tool.

class ToolChoiceTool(TypedDict)

Defined in: src/strands/types/tools.py:120

Configuration for forcing the use of a specific tool.

Attributes:

  • name - The name of the tool that the model must use.
@dataclass
class ToolContext(_Interruptible)

Defined in: src/strands/types/tools.py:131

Context object containing framework-provided data for decorated tools.

This object provides access to framework-level information that may be useful for tool implementations.

Attributes:

  • tool_use - The complete ToolUse object containing tool invocation details.
  • agent - The Agent or BidiAgent instance executing this tool, providing access to conversation history, model configuration, and other agent state.
  • invocation_state - Caller-provided kwargs that were passed to the agent when it was invoked (agent(), agent.invoke_async(), etc.).

Notes:

This class is intended to be instantiated by the SDK. Direct construction by users is not supported and may break in future versions as new fields are added.

Agent or BidiAgent - using Any for backwards compatibility

Configuration for how the model should choose tools.

  • “auto”: The model decides whether to use tools based on the context
  • “any”: The model must use at least one tool (any tool)
  • “tool”: The model must use the specified tool

Callback that runs a single tool and streams back results.

Generator of tool events with the last being the tool result.

class ToolConfig(TypedDict)

Defined in: src/strands/types/tools.py:186

Configuration for tools in a model request.

Attributes:

  • tools - List of tools available to the model.
  • toolChoice - Configuration for how the model should choose tools.
class ToolFunc(Protocol)

Defined in: src/strands/types/tools.py:198

Function signature for Python decorated and module based tools.

def __call__(*args: Any, **kwargs: Any) -> ToolResult | Awaitable[ToolResult]

Defined in: src/strands/types/tools.py:203

Function signature for Python decorated and module based tools.

Returns:

Tool result or awaitable tool result.

class AgentTool(ABC)

Defined in: src/strands/types/tools.py:212

Abstract base class for all SDK tools.

This class defines the interface that all tool implementations must follow. Each tool must provide its name, specification, and implement a stream method that executes the tool’s functionality.

def __init__() -> None

Defined in: src/strands/types/tools.py:221

Initialize the base agent tool with default dynamic state.

@property
@abstractmethod
def tool_name() -> str

Defined in: src/strands/types/tools.py:228

The unique name of the tool used for identification and invocation.

@property
@abstractmethod
def tool_spec() -> ToolSpec

Defined in: src/strands/types/tools.py:235

Tool specification that describes its functionality and parameters.

@property
@abstractmethod
def tool_type() -> str

Defined in: src/strands/types/tools.py:242

The type of the tool implementation (e.g., ‘python’, ‘javascript’, ‘lambda’).

Used for categorization and appropriate handling.

@property
def supports_hot_reload() -> bool

Defined in: src/strands/types/tools.py:250

Whether the tool supports automatic reloading when modified.

Returns:

False by default.

@abstractmethod
def stream(tool_use: ToolUse, invocation_state: dict[str, Any],
**kwargs: Any) -> ToolGenerator

Defined in: src/strands/types/tools.py:260

Stream tool events and return the final result.

Arguments:

  • tool_use - The tool use request containing tool ID and parameters.
  • invocation_state - Caller-provided kwargs that were passed to the agent when it was invoked (agent(), agent.invoke_async(), etc.).
  • **kwargs - Additional keyword arguments for future extensibility.

Yields:

Tool events with the last being the tool result.

@property
def is_dynamic() -> bool

Defined in: src/strands/types/tools.py:275

Whether the tool was dynamically loaded during runtime.

Dynamic tools may have different lifecycle management.

Returns:

True if loaded dynamically, False otherwise.

def mark_dynamic() -> None

Defined in: src/strands/types/tools.py:285

Mark this tool as dynamically loaded.

def get_display_properties() -> dict[str, str]

Defined in: src/strands/types/tools.py:289

Get properties to display in UI representations of this tool.

Subclasses can extend this to include additional properties.

Returns:

Dictionary of property names and their string values.